Background Per- and polyfluoroalkyl substances (PFASs) are a class of persistent organic pollutants that pose potential health risks to humans. Infants and young children have higher requirements for food safety due to the underdeveloped detoxification and immune systems. Therefore, developing a comprehensive method for determination of PFASs and their novel alternatives in infant complementary food is of great significance. Objective To develop an analytical method using liquid chromatography high-resolution mass spectrometry technology for determination of 55 PFASs in plant- and animal-derived infant complementary fruit purees. Methods Oasis WAX (200 mg, 6 CC) solid-phase extraction columns were used for sample enrichment and purification. The pH of the acetonitrile extract was adjusted using 0%, 1%, 1.5%, and 2% formic acid aqueous solutions to evaluate its impact on the recovery rate of target compounds. Additionally, the impact of a 2 mL methanol wash during the purification process on the recovery of target compounds was assessed to determine the optimal pretreatment conditions. Three types of chromatographic columns—Agilent Poroshell 120 EC-C₁₈, Thermo InfinityLab Poroshell 120 Aq-C₁₈, Acquity Waters BEH-C₁₈, and changes in mobile phase, were compared for their effects on retention time, peak shape, and response of target compounds. The method was validated in terms of selectivity, linear range, detection limit, and precision. The established method was applied to 49 commercial samples of infant complementary fruit purees. Results Adjusting the sample pH using 1.5% formic acid water and incorporating a 2 mL methanol wash during purification achieved satisfactory recovery rates. The target compounds were chromatographically separated using an Agilent Poroshell 120 EC-C₁₈ column with a gradient elution system. The mobile phase consisted of methanol-water (methanol/water: 2/98, v/v) containing 5 mmol·L⁻¹ ammonium formate as mobile phase A, and methanol as mobile phase B. Good separation was achieved within 15 min, resulting in optimal chromatographic peak shapes. The 55 target compounds exhibited good linearity across the standard curve range, with correlation coefficients (R²) greater than 0.99. The method detection limits ranged from 0.02 to 0.05 µg·L⁻¹. In the plant- and animal-based fruit puree samples, the spiked recovery rates ranged from 60% to 112% and 57% to 119%, respectively, with relative standard deviations (RSD) ≤ 30%. A total of 9 traditional PFASs and 5 novel PFASs were positive in 49 samples of infant complementary fruit purees. Conclusion This method enables comprehensive detection of 55 traditional and emerging PFASs, offering wide coverage, high accuracy, and excellent sensitivity. It provides technical support for characterizing contamination by traditional and emerging PFASs in food matrices.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background With the progression of industrialization, an increasing number of emerging contaminants are entering aquatic environments, posing significant threats to the safety of drinking water. Therefore, establishing a system for identifying unknown hazardous factors and implementing safety warning mechanisms for drinking water is of paramount importance. Among these efforts, non-target screening plays a critical role, but its effectiveness is largely constrained by the scope of coverage of sample pre-treatment methods. Objective To integrate modern chromatography/mass spectrometry techniques with advanced data mining methods to develop a non-discriminatory sample pre-treatment method for comprehensive enrichment of unknown contaminants in drinking water, laying a technical foundation for the discovery and identification of unknown organic hazardous factors in drinking water. Methods A non-discriminatory pre-treatment method based on supramolecular and solid-phase extraction was developed. The final target compounds including 333 pesticides, 194 pharmaceuticals and personal care products (PPCPs), and 59 per- and polyfluoroalkyl substances (PFASs) were used for optimizing the pre-treatment method, confirming its coverage. The impacts of different eluents on the absolute recovery rates of target compounds were compared to select the conditions with the highest recovery for sample pre-treatment. The effects of different supramolecular solvents and salt concentrations on target compound recovery were also evaluated to determine the most suitable solvent and salt concentration. Results The solid-phase extraction elution solvents, supramolecular extraction solvents, and salt concentrations were optimized based on the target compound recovery rates. The optimal recovery conditions were achieved using 2 mL methanol, 2 mL methanol (containing 1% formic acid), 2 mL ethyl acetate, 2 mL dichloromethane, hexanediol supramolecular solvent, and 426 mg salt. The detection method developed based on these conditions showed a good linear relationship for all target compounds in the range of 0.1-100.0 ng·mL⁻¹, with R² > 0.99. The method’s limit of detection ranged from 0.01 ng⁻¹ to 0.95 ng⁻¹, and 95% of target compounds were recovered in the range of 20%-120%, with relative standard deviation (RSD) less than 30%, indicating good precision. Conclusion The combined pre-treatment method of solid-phase extraction and supramolecular solvent extraction can effectively enrich contaminants in drinking water across low, medium, and high polarities, enabling broad-spectrum enrichment of diverse trace contaminants in drinking water. It provides technical support for broad-spectrum, high-throughput screening and identification of organic pollutants in drinking water, and also serves as a reference for establishing urban drinking water public safety warning systems.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective To explore the clinical efficacy of omacycline(OMC)in the treatment of diabetes mellitus complicated with community-acquired bacterial pneumonia(CABP).Methods Clinical data of T2DM patients with CABP admitted to The First Hospital of Jiaxing from August 2022 to July 2023 were divided into OMC group and non-OMC(NOMC)group according to wheter they received OMC treatment or not.The absorption of pulmonary lesions after treatment,changes in inflammatory indicators[white blood cell count(WBC),C-reactive protein(C-reactive protein,CRP),and anterior calcitonin(procalcitonin,PCT)],comprehensive index[hospitalization days,total hospitalization costs,blood glucose standard within 3 d and glucocorticoid use]and the occurrence of adverse reactions were analyzed and compared.Results A total of 100 diabetes mellitus patients with CABP were included in this study,including 36 cases in OMC group and 64 cases in NOMC group.The absorption of pulmonary inflammation in the OMC group was significantly higher than that in the NOMC group(P<0.05).Before treatment,there was no statistical difference in WBC,CRP and PCT between the two groups(P>0.05).After treatment,WBC,CRP,and PCT in both groups were significantly lower than those before treatment(P<0.05).Furthermore,WBC,CRP,PCT levels,hospital stay,total hospitalization costs and glucocorticoid use rate were significantly lower in the OMC group than in the NOMC group(P<0.05).The blood glucose compliance rate within 3 d in the OMC group was significantly higher than that in the NOMC group(P<0.05).None of the patients had serious complications during the treatment period.Conclusion OMC treatment of T2DM complicated with CABP is helpful for early disease control and rehabilitation,and reduces the treatment burden.

Objective To summarize the clinical experience and risk factors for acute kidney injury (AKI) in neonates undergoing congenital cardiac surgery and demonstrate whether neonatal AKI after cardiac surgery was independently related to perioperative short-term outcomes. Methods Medical records of neonates undergoing congenital heart surgery from January 2014 to September 2021 were retrospectively reviewed. The patients were divided into an AKI group and a non-AKI group according to whether the AKI occured after the surgery. Multivariate logistic analysis was performed to analyze the risk factors for postoperative AKI and the relationship between postoperative AKI and postoperative short-term outcomes. Results A total of 609 patients were included. There were 395 males and 214 females with an age at surgery of 1.0-28.0 d and weight of 1.9-4.8 kg. After cardiac surgery, 139 neonates developed AKI. Multivariate logistic analysis showed that less intraoperative urine output [OR=0.96, 95%CI (0.94, 0.99), P=0.005], more intraoperative infusion of red blood cells [OR=1.49, 95%CI (1.16, 1.91), P=0.002], longer intraoperative deep hypothermic circulatory arrest time [OR=1.02, 95%CI (1.00, 1.04), P=0.020], higher vasoactive-inotropic score [OR=1.03, 95%CI (1.01, 1.04), P<0.001] and elevated lactate (increasing by 5 mmol/L) [OR=2.90, 95%CI (1.76, 4.76), P<0.001] when transferred to ICU were independent risk factors for AKI. AKI was an independent risk factor for increased in-hospital mortality [OR=12.61, 95%CI (3.00, 37.48), P<0.001]. Conclusion Less intraoperative urine output, more intraoperative infusion of red blood cells, longer intraoperative deep hypothermic circulatory arrest time, higher vasoactive-inotropic score and elevated lactate when transferred to ICU are independent risk factors for AKI. Furthermore, AKI is an independent risk factor for perioperative death after cardiac surgery.

Objective To study the ability of radial basis function neural network(RBFNN)with different implementations for electrical impedance tomography(EIT)under real brain shapes,to evaluate the advantages and disadvantages of different approaches,and to provide a reference for the selection of practical imaging methods.Methods COMSOL Multiphysics was used to establish a multilayer 2D model with real structure based on brain CT and an EIT simulation dataset.The effects of the exact RBFNN,the orthogonal least squares-based RBFNN(OLS RBFNN)and the K-Means-based BRFNN(K-Means RBFNN)on the image reconstruction result were explored with the dataset constructed.The root mean square error(RMSE)and image correlation coefficient(ICC)were adopted to evaluate the imaging results.Results EIT could be completed with all the three RBFNNs without noise,and the exact RBFNN had the best results with average ICC and RMSE of 0.784 and 0.467,respectively,in the test set.The OLS RBFNN had the best imaging results at a hidden node of 50,with an average ICC and RMSE of 0.788 and 0.462,respectively.The K-Means RBFNN achieved the best imaging results at noise levels of 30,40,50,60,70 and 80 dB with stable ICC and RMSE and high robustness.Conclusion All the three RBFNNs can be used for brain EIT image reconstruction with their own advantages and disadvantages,and the RBFNN has to be selected for EIT reconstruc-tion based on considerations on actual conditions.[Chinese Medical Equipment Journal,2024,45(10):1-6]

Objective To develop a prediction tool for post-endoscopic retrograde cholangiopancreatography(ER-CP)early biliary tract infection(PEEBI)in patients with choledocholithiasis,and assist clinical decision-making be-fore ERCP and early personalized intervention after ERCP.Methods An observational bidirectional cohort study was adopted to select inpatients with choledocholithiasis who underwent ERCP in a hospital.Directed acyclic graph(DAGs)and the least absolute shrinkage and selection operator(LASSO)were used to predict PEEBI based on lo-gistic regression,and the models were compared and validated internally and externally.Results From January 1,2020 to September 30,2023,a total of 2 121 patients with choledocholithiasis underwent ERCP were enrolled,of whom 77(3.6％)developed PEEBI,mostly in the first 2 days after surgery(66.2％).The major influencing fac-tors for PEEBI were non-iatrogenic patient-related factors,namely diabetes mellitus(OR=2.43,95％CI:1.14-4.85),bile duct malignancy(OR=3.95,95％CI:1.74-8.31)and duodenal papillary diverticulum(OR=4.39,95％CI:1.86-9.52).Compared with the LASSO model,the DAGs model showed higher ability(3.0％)in com-prehensive discrimination(P=0.007),as well as good differentiation performance(D=0.133,P=0.894)and cal-ibration performance(x2=5.499,P=0.703)in external validation.Conclusion The DAGs model constructed in this study has good predictive performance.With the help of this tool,targeted early preventive measures in clinical practice can be taken to reduce the occurrence of PEEBI.